The Real AI Battle Isn't in Chips -- It's in Compute Efficiency. Here's the Stock Positioned to Win.

While investors are looking for who will be the big chip winner in artificial intelligence (AI), that's actually just half the battle. Nvidia (NASDAQ: NVDA) currently dominates the market with its graphics processing units (GPUs), while Advanced Micro Devices (NASDAQ: AMD) has been trying to gain traction in the GPU space and cut into its lead. At the same time, Broadcom (NASDAQ: AVGO) has been helping companies develop their own custom ASICs (application-specific integrated circuits) for AI workloads.

However, as compute efficiency becomes more important, the company best positioned for this environment isn't a pure-play chip company; it's Alphabet (NASDAQ: GOOGL) (NASDAQ: GOOG). Let's look at why the company could be poised to be the big winner in the next phase of AI compute.

Vertical integration will win out

The biggest bottleneck in the world of AI isn't currently a lack of chips; it's a lack of power. That's why compute efficiency is becoming so important. GPUs are great at quickly processing a boatload of data, but they are also energy-hungry. That's justifiable during the training phase of AI, as this is more of a one-time cost. However, as the shift gradually turns to inference, which is an ongoing expense needed to run these large language models (LLMs), compute efficiency becomes much more important.

This is where Alphabet has a big edge. The company has spent more than a decade developing its own custom AI chips designed specifically for its TensorFlow framework. While Broadcom helped and is winning business with other customers, Alphabet's internal efforts should not be overlooked. As companies begin to bring on their own Broadcom-based ASICs, they simply are not going to be able to match Alphabet's Tensor Processing Units (TPUs), which are now in their seventh generation.

The big advantage of Alphabet's TPUs is that they are optimized for Alphabet's cloud computing infrastructure and workloads. This not only helps improve performance, but it also makes its chips more energy efficient, consuming less power. This is a big cost advantage, which should only widen as inference becomes more and more important.

Meanwhile, Alphabet is not selling its TPUs to customers. Instead, for customers to get access to them, they need to run their workloads on Google Cloud. This increases its growth prospects, as it allows it to now capture multiple revenue opportunities within AI.

Also not to be overlooked is the fact that Alphabet is using TPUs to power its own internal AI workloads. By using its own custom chips, Alphabet has a cost advantage in developing and training its Gemini AI model. It also has a cost advantage when running inference for its models, which gives it a structural edge over competitors such as OpenAI and Perplexity AI, which mostly rely on more expensive and power-hungry GPUs.

Image source: Getty Images.

The next stage

As the next stage of AI evolves, Alphabet's vertical integration should put it in a prime position to be the biggest winner. No other company has as complete an AI tech stack as it does. Its recently released Gemini 3 foundation model has garnered widespread praise, with analysts at D.A. Davidson saying it has "capabilities that in certain areas far exceed what we've typically come to expect from this generation of frontier models."

Meanwhile, Nvidia's recent investment spree in its own customers can be traced back to news that OpenAI was starting to test TPUs for its workloads. According to The Wall Street Journal, after that news came out, Nvidia rushed back to strike a deal with OpenAI and make an investment in the AI model start-up. That reaction shows the respect Nvidia has for Alphabet's TPUs.

Alphabet also has top software platforms, such as Vertex AI, to help customers create their own AI models and apps based on its Gemini model, and even its own massive fiber network, to reduce latency. Its pending acquisition of leading cloud security company Wiz will only add to its AI tech stack.

Given this, if I could only bet on one AI stock over the long term, I'd choose Alphabet.

Geoffrey Seiler has positions in Alphabet. The Motley Fool has positions in and recommends Advanced Micro Devices, Alphabet, and Nvidia. The Motley Fool recommends Broadcom. The Motley Fool has a disclosure policy.